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Previous work on introns and code growth in genetic programming is expanded on and tested experimentally. Explicitly defined introns are introduced to tree-based representations as an aid to measuring and evaluating intron behavior. Although it is shown that introns do create code growth, they are not its only cause. Removing introns merely decreases the growth rate; it does not eliminate it. By systematically negating various forms of intron behavior, a deeper understanding of the causes of code growth is obtained, leading to the development of a system that keeps unnecessary bloat to a minimum. Alternative selection schemes and recombination operators are examined and improvements demonstrated over the standard selection methods in terms of both performance and parsimony.

This article reports three related studies which investigate how undergraduates use and think about information and communication technologies (ICT) in the context of learning at university. Data were obtained via questionnaires, computer diary records and focus group discussions. The studies were intended to help universities decide how to incorporate ICT into student learning, how the cost of equipment should be shared between students and institutions, and how university provision should be organised to best t student needs, attitudes and perceptions. Presentation of the results from the studies is followed by a discussion, which attempts to draw out the practical implications of the evaluation evidence for university policy-makers.